Package: propagate 1.0-6

Andrej-Nikolai Spiess

propagate: Propagation of Uncertainty

Propagation of uncertainty using higher-order Taylor expansion and Monte Carlo simulation.

Authors:Andrej-Nikolai Spiess <[email protected]>

propagate_1.0-6.tar.gz
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propagate_1.0-6.tgz(r-4.4-emscripten)propagate_1.0-6.tgz(r-4.3-emscripten)
propagate.pdf |propagate.html✨
propagate/json (API)
NEWS

# Install 'propagate' in R:
install.packages('propagate', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • H.2 - Datasets from the GUM "Guide to the expression of uncertainties in measurement"
  • H.3 - Datasets from the GUM "Guide to the expression of uncertainties in measurement"
  • H.4 - Datasets from the GUM "Guide to the expression of uncertainties in measurement"

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

4.81 score 2 stars 3 packages 181 scripts 466 downloads 4 mentions 20 exports 12 dependencies

Last updated 7 years agofrom:b438193066. Checks:1 OK, 1 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 21 2025
R-4.5-linux-x86_64NOTEJan 21 2025

Exports:bigcorcolVarsCcor2covevalDerivsfitDistrintervalkurtosismakeDatmakeGradmakeHessmixCovnumGradnumHesspredictNLSpropagaterowVarsCskewnessstatVecstochContrWelchSatter

Dependencies:bitffgmmlatticeMASSMatrixminpack.lmmvtnormRcppsandwichtmvtnormzoo

Readme and manuals

Help Manual

Help pageTopics
Creating very large correlation/covariance matricesbigcor
Converting a correlation matrix into a covariance matrixcor2cov
Datasets from the GUM "Guide to the expression of uncertainties in measurement" (2008)H.2 H.3 H.4
Fitting distributions to observations/Monte Carlo simulationsfitDistr
Uncertainty propagation based on interval arithmeticsinterval
Create a dataframe from the variables defined in an expressionmakeDat
Utility functions for creating Gradient- and Hessian-like matrices with symbolic derivatives and evaluating them in an environmentevalDerivs makeGrad makeHess
Fast column- and row-wise versions of variance coded in C++colVarsC rowVarsC
Aggregating covariances matrices and/or error vectors into a single covariance matrixmixCov
Skewness and (excess) Kurtosis of a vector of valueskurtosis skewness
Functions for creating Gradient and Hessian matrices by numerical differentiation (Richardson's method) of the partial derivativesnumGrad numHess
Plotting function for 'propagate' objectsplot.propagate
Confidence/prediction intervals for (weighted) nonlinear models based on uncertainty propagationpredictNLS
Propagation of uncertainty using higher-order Taylor expansion and Monte Carlo simulationpropagate
Creating random samples from a variety of useful distributionsrDistr
Transform an input vector into one with defined mean and standard deviationstatVec
Stochastic contribution analysis of Monte Carlo simulation-derived propagated uncertaintystochContr
Summary function for 'propagate' objectssummary.propagate
Welch-Satterthwaite approximation to the 'effective degrees of freedom'WelchSatter